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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 19 citing articles:

Assessing the significance of the particle size of Ganga sand Sone sand and bentonite mixtures for hydraulic containment liners integrated with machine learning-based UCS predictions
Rajiv Kumar, Divesh Ranjan Kumar, Sunita Kumari, et al.
Construction and Building Materials (2025) Vol. 465, pp. 140236-140236
Closed Access | Times Cited: 1
Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack detection and concrete property exploration
Kaustav Sarkar, Amit Shiuly, Krishna Gopal Dhal
Construction and Building Materials (2023) Vol. 411, pp. 134212-134212
Closed Access | Times Cited: 32
Estimation of compressive strength for spiral stirrup-confined circular concrete column using optimized machine learning with interpretable techniques
Yang Sun
Mechanics of Advanced Materials and Structures (2024), pp. 1-20
Closed Access | Times Cited: 11
Artificial intelligence models for predicting unconfined compressive strength of mixed soil types: focusing on clay and sand
Barada Prasad Sethy, Umashankar Prajapati, K Neelashetty, et al.
Asian Journal of Civil Engineering (2025)
Closed Access
Evaluating the rapid chloride permeability of self-compacting concrete containing fly ash and silica fume exposed to different temperatures: An artificial intelligence framework
Ramin Kazemi, Aliakbar Gholampour
Construction and Building Materials (2023) Vol. 409, pp. 133835-133835
Closed Access | Times Cited: 12
A hybrid artificial intelligence approach for modeling the carbonation depth of sustainable concrete containing fly ash
Ramin Kazemi
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Advancing mix design prediction in 3D printed concrete: Predicting anisotropic compressive strength and slump flow
Umair Jalil Malik, Raja Dilawar Riaz, Saif Ur Rehman, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03510-e03510
Open Access | Times Cited: 4
Innovative enhancement of self-compacting concrete using varying percentages of steel slag: an experimental investigation into fresh, mechanical, durability, and microstructural properties
Sabhilesh Singh, Vivek Anand
Asian Journal of Civil Engineering (2024)
Closed Access | Times Cited: 2
Compressive strength prediction of sustainable concrete containing waste foundry sand using metaheuristic optimization‐based hybrid artificial neural network
Ramin Kazemi, Emadaldin Mohammadi Golafshani, Ali Behnood
Structural Concrete (2023) Vol. 25, Iss. 2, pp. 1343-1363
Closed Access | Times Cited: 7
Assessing the compressive strength of eco-friendly concrete made with rice husk ash: A hybrid artificial intelligence-aided technique
Ramin Kazemi, Seyed Ali Emamian, Mehrdad Arashpour
Structures (2024) Vol. 68, pp. 107050-107050
Closed Access | Times Cited: 2
Advancements in AI-Based Information Technologies: Solutions for Quality and Security
Tetiana Hovorushchenko, Ivan Izonin, Hakan Kutucu
Systems (2024) Vol. 12, Iss. 2, pp. 58-58
Open Access | Times Cited: 1
Bibliometric and Scientometric Trends in Structural Health Monitoring Using Fiber-Optic Sensors: A Comprehensive Review
Khairil Mahbubi, Ahmad Zaki, Guntur Nugroho
Journal of Civil and Hydraulic Engineering (2024) Vol. 2, Iss. 1, pp. 51-64
Open Access | Times Cited: 1
Effect of soil characteristics on compressive strength of cement stabilized earth blocks: Statistical analysis and Artificial Neural Networks model
Navaratnarajah Sathiparan, Pratheeba Jeyananthan
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Artificial Neural Network-Based Prediction of Physical and Mechanical Properties of Concrete Containing Glass Aggregates
Faroq Maraqa, Amjad A. Yasin, Eid Al-Sahawneh, et al.
Civil Engineering Journal (2024) Vol. 10, Iss. 5, pp. 1627-1644
Open Access | Times Cited: 1
Cyclic performance of precast hollow core slab to beam connections using innovative assembling technique
D. Vinutha, R. Vidjeapriya
Soil Dynamics and Earthquake Engineering (2024) Vol. 183, pp. 108816-108816
Closed Access | Times Cited: 1
Mapping Publications of Cracks Monitoring in Concrete Structures: Bibliometric and Scientometric Review in 2013-2023
Kharisma Wira Nindhita, Ahmad Zaki, Guntur Nugroho
Annales de Chimie Science des Matériaux (2024) Vol. 48, Iss. 4, pp. 467-479
Open Access | Times Cited: 1
Compressive strength prediction of nano-modified concrete: A comparative study of advanced machine learning techniques
X.M. Tao
AIP Advances (2024) Vol. 14, Iss. 7
Open Access
Study on bending fatigue performance of recycled aggregate backfill subgrade
Zehui Chen, Xiaowei Feng, Fang Xinjun, et al.
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access
An AI-driven approach for modeling the compressive strength of sustainable concrete incorporating waste marble as an industrial by-product
Ramin Kazemi, Seyedali Mirjalili
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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